Overview

Brought to you by YData

Dataset statistics

Number of variables24
Number of observations500000
Missing cells2252884
Missing cells (%)18.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory616.5 MiB
Average record size in memory1.3 KiB

Variable types

Numeric4
Categorical10
Text4
DateTime6

Alerts

question_language has constant value "eng"Constant
question_user_type has constant value "farmer"Constant
response_user_type has constant value "farmer"Constant
question_id is highly overall correlated with question_user_id and 2 other fieldsHigh correlation
question_user_country_code is highly overall correlated with response_user_country_codeHigh correlation
question_user_id is highly overall correlated with question_id and 1 other fieldsHigh correlation
response_id is highly overall correlated with question_id and 2 other fieldsHigh correlation
response_user_country_code is highly overall correlated with question_user_country_codeHigh correlation
response_user_id is highly overall correlated with question_id and 1 other fieldsHigh correlation
response_language is highly imbalanced (88.8%)Imbalance
question_topic has 67186 (13.4%) missing valuesMissing
response_topic has 328854 (65.8%) missing valuesMissing
question_user_gender has 480094 (96.0%) missing valuesMissing
question_user_dob has 462710 (92.5%) missing valuesMissing
response_user_gender has 466152 (93.2%) missing valuesMissing
response_user_dob has 447888 (89.6%) missing valuesMissing

Reproduction

Analysis started2025-11-06 14:26:33.238249
Analysis finished2025-11-06 14:27:54.582144
Duration1 minute and 21.34 seconds
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

question_id
Real number (ℝ)

High correlation 

Distinct428151
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27264997
Minimum3849153
Maximum59254650
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2025-11-06T14:27:54.719229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3849153
5-th percentile6469463.8
Q114135594
median23611586
Q340509218
95-th percentile56091867
Maximum59254650
Range55405497
Interquartile range (IQR)26373624

Descriptive statistics

Standard deviation15686339
Coefficient of variation (CV)0.57532881
Kurtosis-1.0098993
Mean27264997
Median Absolute Deviation (MAD)11914470
Skewness0.4396718
Sum1.3632499 × 1013
Variance2.4606122 × 1014
MonotonicityNot monotonic
2025-11-06T14:27:54.866576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56318162136
 
< 0.1%
5907694490
 
< 0.1%
4300117983
 
< 0.1%
4282049983
 
< 0.1%
5901328581
 
< 0.1%
5157734377
 
< 0.1%
3161368866
 
< 0.1%
5908718863
 
< 0.1%
5868987850
 
< 0.1%
4263449347
 
< 0.1%
Other values (428141)499224
99.8%
ValueCountFrequency (%)
38491531
< 0.1%
38492751
< 0.1%
38498941
< 0.1%
38513301
< 0.1%
38515631
< 0.1%
38524331
< 0.1%
38524581
< 0.1%
38527891
< 0.1%
38532712
< 0.1%
38533051
< 0.1%
ValueCountFrequency (%)
592546501
< 0.1%
592541961
< 0.1%
592540471
< 0.1%
592539611
< 0.1%
592537911
< 0.1%
592537661
< 0.1%
592533741
< 0.1%
592531161
< 0.1%
592530351
< 0.1%
592522971
< 0.1%

question_user_id
Real number (ℝ)

High correlation 

Distinct186897
Distinct (%)37.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1561144.6
Minimum7
Maximum3826307
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2025-11-06T14:27:55.016411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile159020
Q1868627
median1337141
Q32217046
95-th percentile3363425
Maximum3826307
Range3826300
Interquartile range (IQR)1348419

Descriptive statistics

Standard deviation970567.66
Coefficient of variation (CV)0.62170261
Kurtosis-0.71110304
Mean1561144.6
Median Absolute Deviation (MAD)633650
Skewness0.49109575
Sum7.8057229 × 1011
Variance9.4200157 × 1011
MonotonicityNot monotonic
2025-11-06T14:27:55.176868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
730226978
 
0.2%
3413249861
 
0.2%
3199006797
 
0.2%
853100570
 
0.1%
1061058554
 
0.1%
1206146425
 
0.1%
679197415
 
0.1%
607370396
 
0.1%
3065420386
 
0.1%
793767383
 
0.1%
Other values (186887)494235
98.8%
ValueCountFrequency (%)
71
 
< 0.1%
192
 
< 0.1%
202
 
< 0.1%
261
 
< 0.1%
295
< 0.1%
885
< 0.1%
951
 
< 0.1%
1222
 
< 0.1%
1611
 
< 0.1%
1731
 
< 0.1%
ValueCountFrequency (%)
38263071
 
< 0.1%
38245462
< 0.1%
38240321
 
< 0.1%
38240141
 
< 0.1%
38229811
 
< 0.1%
38194731
 
< 0.1%
38180591
 
< 0.1%
38156271
 
< 0.1%
38145681
 
< 0.1%
38125314
< 0.1%

question_language
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 MiB
eng
500000 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1500000
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st roweng
2nd roweng
3rd roweng
4th roweng
5th roweng

Common Values

ValueCountFrequency (%)
eng500000
100.0%

Length

2025-11-06T14:27:55.316638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-06T14:27:55.417185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
eng500000
100.0%

Most occurring characters

ValueCountFrequency (%)
e500000
33.3%
n500000
33.3%
g500000
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)1500000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e500000
33.3%
n500000
33.3%
g500000
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1500000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e500000
33.3%
n500000
33.3%
g500000
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1500000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e500000
33.3%
n500000
33.3%
g500000
33.3%
Distinct416521
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size59.4 MiB
2025-11-06T14:27:55.758796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length626
Median length387
Mean length59.075224
Min length8

Characters and Unicode

Total characters29537612
Distinct characters139
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique358953 ?
Unique (%)71.8%

Sample

1st rowQ What vaccine can I use for my two weeks poultry
2nd rowDo we have banana hybrid in Uganda
3rd rowQ hoW TO PLANT CABBAGE
4th rowDononzio asks: my cow has aproblm it cann,t bleast feed their young one what can i do. Reply Q435 followed by your response. optout stop 6333
5th rowQ WHAT IS THE CORRECT AMOUNT OF A SIX ACRE LAND -FERTILIZER.
ValueCountFrequency (%)
q217145
 
3.8%
to171446
 
3.0%
i168847
 
2.9%
is163195
 
2.8%
the157227
 
2.7%
of152917
 
2.7%
what129821
 
2.3%
in126044
 
2.2%
can117963
 
2.1%
how104824
 
1.8%
Other values (135304)4222701
73.7%
2025-11-06T14:27:56.522910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5379160
18.2%
e2246938
 
7.6%
a1950351
 
6.6%
t1726840
 
5.8%
o1650091
 
5.6%
i1488872
 
5.0%
n1383858
 
4.7%
s1315173
 
4.5%
r1085219
 
3.7%
h1038311
 
3.5%
Other values (129)10272799
34.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)29537612
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5379160
18.2%
e2246938
 
7.6%
a1950351
 
6.6%
t1726840
 
5.8%
o1650091
 
5.6%
i1488872
 
5.0%
n1383858
 
4.7%
s1315173
 
4.5%
r1085219
 
3.7%
h1038311
 
3.5%
Other values (129)10272799
34.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)29537612
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5379160
18.2%
e2246938
 
7.6%
a1950351
 
6.6%
t1726840
 
5.8%
o1650091
 
5.6%
i1488872
 
5.0%
n1383858
 
4.7%
s1315173
 
4.5%
r1085219
 
3.7%
h1038311
 
3.5%
Other values (129)10272799
34.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)29537612
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5379160
18.2%
e2246938
 
7.6%
a1950351
 
6.6%
t1726840
 
5.8%
o1650091
 
5.6%
i1488872
 
5.0%
n1383858
 
4.7%
s1315173
 
4.5%
r1085219
 
3.7%
h1038311
 
3.5%
Other values (129)10272799
34.8%

question_topic
Text

Missing 

Distinct147
Distinct (%)< 0.1%
Missing67186
Missing (%)13.4%
Memory size31.8 MiB
2025-11-06T14:27:56.782066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length5.7172758
Min length3

Characters and Unicode

Total characters2474517
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowpoultry
2nd rowbanana
3rd rowcabbage
4th rowcattle
5th rowcattle
ValueCountFrequency (%)
cattle48109
 
11.1%
maize46682
 
10.8%
chicken43856
 
10.1%
plant39383
 
9.1%
tomato24043
 
5.6%
crop23050
 
5.3%
bean17287
 
4.0%
banana13485
 
3.1%
pig12413
 
2.9%
poultry11662
 
2.7%
Other values (137)152844
35.3%
2025-11-06T14:27:57.188551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a353038
14.3%
t280987
11.4%
e269351
10.9%
c202093
 
8.2%
n179027
 
7.2%
o165524
 
6.7%
i156507
 
6.3%
l140340
 
5.7%
p123988
 
5.0%
m94476
 
3.8%
Other values (17)509186
20.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)2474517
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a353038
14.3%
t280987
11.4%
e269351
10.9%
c202093
 
8.2%
n179027
 
7.2%
o165524
 
6.7%
i156507
 
6.3%
l140340
 
5.7%
p123988
 
5.0%
m94476
 
3.8%
Other values (17)509186
20.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)2474517
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a353038
14.3%
t280987
11.4%
e269351
10.9%
c202093
 
8.2%
n179027
 
7.2%
o165524
 
6.7%
i156507
 
6.3%
l140340
 
5.7%
p123988
 
5.0%
m94476
 
3.8%
Other values (17)509186
20.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)2474517
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a353038
14.3%
t280987
11.4%
e269351
10.9%
c202093
 
8.2%
n179027
 
7.2%
o165524
 
6.7%
i156507
 
6.3%
l140340
 
5.7%
p123988
 
5.0%
m94476
 
3.8%
Other values (17)509186
20.6%
Distinct428132
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
Minimum2017-11-22 12:25:18+00:00
Maximum2022-04-07 13:24:35.649166+00:00
Invalid dates0
Invalid dates (%)0.0%
2025-11-06T14:27:57.359469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:57.513341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

response_id
Real number (ℝ)

High correlation 

Distinct491737
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27465654
Minimum3849219
Maximum59257380
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2025-11-06T14:27:57.666974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3849219
5-th percentile6603242.7
Q114314404
median23844892
Q340725535
95-th percentile56302021
Maximum59257380
Range55408161
Interquartile range (IQR)26411132

Descriptive statistics

Standard deviation15711650
Coefficient of variation (CV)0.57204719
Kurtosis-1.0220912
Mean27465654
Median Absolute Deviation (MAD)11996184
Skewness0.43113889
Sum1.3732827 × 1013
Variance2.4685595 × 1014
MonotonicityNot monotonic
2025-11-06T14:27:57.813668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
235091398
 
< 0.1%
196400358
 
< 0.1%
343849036
 
< 0.1%
428795926
 
< 0.1%
141622125
 
< 0.1%
147650805
 
< 0.1%
203868485
 
< 0.1%
163683685
 
< 0.1%
153799165
 
< 0.1%
226813545
 
< 0.1%
Other values (491727)499942
> 99.9%
ValueCountFrequency (%)
38492191
< 0.1%
38507201
< 0.1%
38516941
< 0.1%
38525511
< 0.1%
38533361
< 0.1%
38533381
< 0.1%
38536161
< 0.1%
38536511
< 0.1%
38537821
< 0.1%
38538921
< 0.1%
ValueCountFrequency (%)
592573801
< 0.1%
592566031
< 0.1%
592558941
< 0.1%
592547461
< 0.1%
592546801
< 0.1%
592546101
< 0.1%
592545891
< 0.1%
592544511
< 0.1%
592542811
< 0.1%
592542741
< 0.1%

response_user_id
Real number (ℝ)

High correlation 

Distinct154989
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1352732.7
Minimum20
Maximum3830610
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 MiB
2025-11-06T14:27:57.964454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile96341
Q1651207
median1171500
Q31943918
95-th percentile3186456.4
Maximum3830610
Range3830590
Interquartile range (IQR)1292711

Descriptive statistics

Standard deviation926721.66
Coefficient of variation (CV)0.68507373
Kurtosis-0.38490513
Mean1352732.7
Median Absolute Deviation (MAD)652556
Skewness0.65113542
Sum6.7636637 × 1011
Variance8.5881304 × 1011
MonotonicityNot monotonic
2025-11-06T14:27:58.127250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1364605950
 
0.2%
3413249789
 
0.2%
367428552
 
0.1%
1254217450
 
0.1%
3065420448
 
0.1%
202949391
 
0.1%
1149700387
 
0.1%
478338384
 
0.1%
1053962379
 
0.1%
1151861357
 
0.1%
Other values (154979)494913
99.0%
ValueCountFrequency (%)
205
 
< 0.1%
262
 
< 0.1%
2919
< 0.1%
322
 
< 0.1%
8818
< 0.1%
923
 
< 0.1%
954
 
< 0.1%
1202
 
< 0.1%
1223
 
< 0.1%
1422
 
< 0.1%
ValueCountFrequency (%)
38306101
 
< 0.1%
38284254
< 0.1%
38125312
< 0.1%
38106141
 
< 0.1%
37988501
 
< 0.1%
37930141
 
< 0.1%
37757151
 
< 0.1%
37744774
< 0.1%
37681991
 
< 0.1%
37565231
 
< 0.1%

response_language
Categorical

Imbalance 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.4 MiB
eng
481057 
swa
 
16273
lug
 
1351
nyn
 
1316
spa
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1500000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st roweng
2nd roweng
3rd roweng
4th roweng
5th roweng

Common Values

ValueCountFrequency (%)
eng481057
96.2%
swa16273
 
3.3%
lug1351
 
0.3%
nyn1316
 
0.3%
spa3
 
< 0.1%

Length

2025-11-06T14:27:58.274453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-06T14:27:58.380234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
eng481057
96.2%
swa16273
 
3.3%
lug1351
 
0.3%
nyn1316
 
0.3%
spa3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
n483689
32.2%
g482408
32.2%
e481057
32.1%
s16276
 
1.1%
a16276
 
1.1%
w16273
 
1.1%
l1351
 
0.1%
u1351
 
0.1%
y1316
 
0.1%
p3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)1500000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n483689
32.2%
g482408
32.2%
e481057
32.1%
s16276
 
1.1%
a16276
 
1.1%
w16273
 
1.1%
l1351
 
0.1%
u1351
 
0.1%
y1316
 
0.1%
p3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1500000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n483689
32.2%
g482408
32.2%
e481057
32.1%
s16276
 
1.1%
a16276
 
1.1%
w16273
 
1.1%
l1351
 
0.1%
u1351
 
0.1%
y1316
 
0.1%
p3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1500000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n483689
32.2%
g482408
32.2%
e481057
32.1%
s16276
 
1.1%
a16276
 
1.1%
w16273
 
1.1%
l1351
 
0.1%
u1351
 
0.1%
y1316
 
0.1%
p3
 
< 0.1%
Distinct479494
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size54.1 MiB
2025-11-06T14:27:58.915425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length935
Median length703
Mean length47.799758
Min length1

Characters and Unicode

Total characters23899879
Distinct characters153
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique467424 ?
Unique (%)93.5%

Sample

1st rowVaccinate against foul pox and coccidiosis
2nd rowQ108 Yes In Bushenyi District
3rd rowQ129 Just like sukumawiki, cabbages take the same process to plant.
4th rowAt fast provide bucket feeding and consult the veterinary.
5th rowQ856 60KGS
ValueCountFrequency (%)
the118077
 
2.8%
and89218
 
2.1%
of84517
 
2.0%
to79881
 
1.9%
is68289
 
1.6%
in59594
 
1.4%
it53705
 
1.3%
a44629
 
1.0%
you37964
 
0.9%
for33488
 
0.8%
Other values (284471)3591439
84.3%
2025-11-06T14:27:59.612568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3861932
16.2%
e1863114
 
7.8%
a1407386
 
5.9%
t1286787
 
5.4%
o1176913
 
4.9%
i1128189
 
4.7%
n1123922
 
4.7%
s1050551
 
4.4%
r982996
 
4.1%
l646189
 
2.7%
Other values (143)9371900
39.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)23899879
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3861932
16.2%
e1863114
 
7.8%
a1407386
 
5.9%
t1286787
 
5.4%
o1176913
 
4.9%
i1128189
 
4.7%
n1123922
 
4.7%
s1050551
 
4.4%
r982996
 
4.1%
l646189
 
2.7%
Other values (143)9371900
39.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)23899879
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3861932
16.2%
e1863114
 
7.8%
a1407386
 
5.9%
t1286787
 
5.4%
o1176913
 
4.9%
i1128189
 
4.7%
n1123922
 
4.7%
s1050551
 
4.4%
r982996
 
4.1%
l646189
 
2.7%
Other values (143)9371900
39.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)23899879
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3861932
16.2%
e1863114
 
7.8%
a1407386
 
5.9%
t1286787
 
5.4%
o1176913
 
4.9%
i1128189
 
4.7%
n1123922
 
4.7%
s1050551
 
4.4%
r982996
 
4.1%
l646189
 
2.7%
Other values (143)9371900
39.2%

response_topic
Text

Missing 

Distinct148
Distinct (%)0.1%
Missing328854
Missing (%)65.8%
Memory size24.1 MiB
2025-11-06T14:27:59.855456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length5.6520748
Min length3

Characters and Unicode

Total characters967330
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowplant
2nd rowmaize
3rd rowwheat
4th rowwheat
5th rowplant
ValueCountFrequency (%)
plant21003
 
12.3%
chicken15604
 
9.1%
cattle14587
 
8.5%
maize13128
 
7.7%
crop11732
 
6.9%
animal7933
 
4.6%
bean7068
 
4.1%
tomato5066
 
3.0%
banana4491
 
2.6%
potato3801
 
2.2%
Other values (138)66733
39.0%
2025-11-06T14:28:00.241601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a139190
14.4%
e100536
10.4%
t96685
10.0%
n78002
 
8.1%
c76303
 
7.9%
l62330
 
6.4%
i59239
 
6.1%
o57711
 
6.0%
p55518
 
5.7%
r40145
 
4.2%
Other values (17)201671
20.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)967330
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a139190
14.4%
e100536
10.4%
t96685
10.0%
n78002
 
8.1%
c76303
 
7.9%
l62330
 
6.4%
i59239
 
6.1%
o57711
 
6.0%
p55518
 
5.7%
r40145
 
4.2%
Other values (17)201671
20.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)967330
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a139190
14.4%
e100536
10.4%
t96685
10.0%
n78002
 
8.1%
c76303
 
7.9%
l62330
 
6.4%
i59239
 
6.1%
o57711
 
6.0%
p55518
 
5.7%
r40145
 
4.2%
Other values (17)201671
20.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)967330
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a139190
14.4%
e100536
10.4%
t96685
10.0%
n78002
 
8.1%
c76303
 
7.9%
l62330
 
6.4%
i59239
 
6.1%
o57711
 
6.0%
p55518
 
5.7%
r40145
 
4.2%
Other values (17)201671
20.8%
Distinct491721
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
Minimum2017-11-22 12:28:53+00:00
Maximum2022-04-24 09:51:30.725947+00:00
Invalid dates0
Invalid dates (%)0.0%
2025-11-06T14:28:00.387947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:28:00.533491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

question_user_type
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.9 MiB
farmer
500000 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters3000000
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfarmer
2nd rowfarmer
3rd rowfarmer
4th rowfarmer
5th rowfarmer

Common Values

ValueCountFrequency (%)
farmer500000
100.0%

Length

2025-11-06T14:28:00.665734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-06T14:28:00.758259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
farmer500000
100.0%

Most occurring characters

ValueCountFrequency (%)
r1000000
33.3%
f500000
16.7%
a500000
16.7%
m500000
16.7%
e500000
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)3000000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r1000000
33.3%
f500000
16.7%
a500000
16.7%
m500000
16.7%
e500000
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)3000000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r1000000
33.3%
f500000
16.7%
a500000
16.7%
m500000
16.7%
e500000
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)3000000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r1000000
33.3%
f500000
16.7%
a500000
16.7%
m500000
16.7%
e500000
16.7%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.4 MiB
live
316883 
zombie
109953 
destroyed
45890 
blocked
 
27274

Length

Max length9
Median length4
Mean length5.062356
Min length4

Characters and Unicode

Total characters2531178
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowzombie
2nd rowlive
3rd rowlive
4th rowzombie
5th rowzombie

Common Values

ValueCountFrequency (%)
live316883
63.4%
zombie109953
 
22.0%
destroyed45890
 
9.2%
blocked27274
 
5.5%

Length

2025-11-06T14:28:00.864806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-06T14:28:00.973257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
live316883
63.4%
zombie109953
 
22.0%
destroyed45890
 
9.2%
blocked27274
 
5.5%

Most occurring characters

ValueCountFrequency (%)
e545890
21.6%
i426836
16.9%
l344157
13.6%
v316883
12.5%
o183117
 
7.2%
b137227
 
5.4%
d119054
 
4.7%
z109953
 
4.3%
m109953
 
4.3%
s45890
 
1.8%
Other values (5)192218
 
7.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)2531178
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e545890
21.6%
i426836
16.9%
l344157
13.6%
v316883
12.5%
o183117
 
7.2%
b137227
 
5.4%
d119054
 
4.7%
z109953
 
4.3%
m109953
 
4.3%
s45890
 
1.8%
Other values (5)192218
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)2531178
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e545890
21.6%
i426836
16.9%
l344157
13.6%
v316883
12.5%
o183117
 
7.2%
b137227
 
5.4%
d119054
 
4.7%
z109953
 
4.3%
m109953
 
4.3%
s45890
 
1.8%
Other values (5)192218
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)2531178
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e545890
21.6%
i426836
16.9%
l344157
13.6%
v316883
12.5%
o183117
 
7.2%
b137227
 
5.4%
d119054
 
4.7%
z109953
 
4.3%
m109953
 
4.3%
s45890
 
1.8%
Other values (5)192218
 
7.6%

question_user_country_code
Categorical

High correlation 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.9 MiB
ke
313338 
ug
186641 
gb
 
21

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1000000
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowug
2nd rowug
3rd rowke
4th rowug
5th rowke

Common Values

ValueCountFrequency (%)
ke313338
62.7%
ug186641
37.3%
gb21
 
< 0.1%

Length

2025-11-06T14:28:01.090068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-06T14:28:01.191710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ke313338
62.7%
ug186641
37.3%
gb21
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
k313338
31.3%
e313338
31.3%
g186662
18.7%
u186641
18.7%
b21
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)1000000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
k313338
31.3%
e313338
31.3%
g186662
18.7%
u186641
18.7%
b21
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1000000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
k313338
31.3%
e313338
31.3%
g186662
18.7%
u186641
18.7%
b21
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1000000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
k313338
31.3%
e313338
31.3%
g186662
18.7%
u186641
18.7%
b21
 
< 0.1%

question_user_gender
Categorical

Missing 

Distinct2
Distinct (%)< 0.1%
Missing480094
Missing (%)96.0%
Memory size34.3 MiB
male
15903 
female
4003 

Length

Max length6
Median length4
Mean length4.4021903
Min length4

Characters and Unicode

Total characters87630
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowmale
2nd rowfemale
3rd rowmale
4th rowmale
5th rowmale

Common Values

ValueCountFrequency (%)
male15903
 
3.2%
female4003
 
0.8%
(Missing)480094
96.0%

Length

2025-11-06T14:28:01.320840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-06T14:28:01.436916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
male15903
79.9%
female4003
 
20.1%

Most occurring characters

ValueCountFrequency (%)
e23909
27.3%
m19906
22.7%
a19906
22.7%
l19906
22.7%
f4003
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)87630
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e23909
27.3%
m19906
22.7%
a19906
22.7%
l19906
22.7%
f4003
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)87630
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e23909
27.3%
m19906
22.7%
a19906
22.7%
l19906
22.7%
f4003
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)87630
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e23909
27.3%
m19906
22.7%
a19906
22.7%
l19906
22.7%
f4003
 
4.6%

question_user_dob
Date

Missing 

Distinct6936
Distinct (%)18.6%
Missing462710
Missing (%)92.5%
Memory size7.6 MiB
Minimum1917-12-07 00:00:00
Maximum2020-08-27 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-11-06T14:28:01.827792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:28:01.978738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct185859
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
Minimum2014-11-27 16:15:53+00:00
Maximum2022-03-26 11:57:31.241786+00:00
Invalid dates0
Invalid dates (%)0.0%
2025-11-06T14:28:02.121257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:28:02.269604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

response_user_type
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.9 MiB
farmer
500000 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters3000000
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfarmer
2nd rowfarmer
3rd rowfarmer
4th rowfarmer
5th rowfarmer

Common Values

ValueCountFrequency (%)
farmer500000
100.0%

Length

2025-11-06T14:28:02.402424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-06T14:28:02.501182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
farmer500000
100.0%

Most occurring characters

ValueCountFrequency (%)
r1000000
33.3%
f500000
16.7%
a500000
16.7%
m500000
16.7%
e500000
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)3000000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r1000000
33.3%
f500000
16.7%
a500000
16.7%
m500000
16.7%
e500000
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)3000000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r1000000
33.3%
f500000
16.7%
a500000
16.7%
m500000
16.7%
e500000
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)3000000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r1000000
33.3%
f500000
16.7%
a500000
16.7%
m500000
16.7%
e500000
16.7%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.4 MiB
live
332948 
zombie
83199 
destroyed
61325 
blocked
 
22528

Length

Max length9
Median length4
Mean length5.081214
Min length4

Characters and Unicode

Total characters2540607
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowzombie
2nd rowlive
3rd rowlive
4th rowzombie
5th rowlive

Common Values

ValueCountFrequency (%)
live332948
66.6%
zombie83199
 
16.6%
destroyed61325
 
12.3%
blocked22528
 
4.5%

Length

2025-11-06T14:28:02.609696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-06T14:28:02.746822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
live332948
66.6%
zombie83199
 
16.6%
destroyed61325
 
12.3%
blocked22528
 
4.5%

Most occurring characters

ValueCountFrequency (%)
e561325
22.1%
i416147
16.4%
l355476
14.0%
v332948
13.1%
o167052
 
6.6%
d145178
 
5.7%
b105727
 
4.2%
z83199
 
3.3%
m83199
 
3.3%
s61325
 
2.4%
Other values (5)229031
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)2540607
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e561325
22.1%
i416147
16.4%
l355476
14.0%
v332948
13.1%
o167052
 
6.6%
d145178
 
5.7%
b105727
 
4.2%
z83199
 
3.3%
m83199
 
3.3%
s61325
 
2.4%
Other values (5)229031
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)2540607
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e561325
22.1%
i416147
16.4%
l355476
14.0%
v332948
13.1%
o167052
 
6.6%
d145178
 
5.7%
b105727
 
4.2%
z83199
 
3.3%
m83199
 
3.3%
s61325
 
2.4%
Other values (5)229031
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)2540607
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e561325
22.1%
i416147
16.4%
l355476
14.0%
v332948
13.1%
o167052
 
6.6%
d145178
 
5.7%
b105727
 
4.2%
z83199
 
3.3%
m83199
 
3.3%
s61325
 
2.4%
Other values (5)229031
9.0%

response_user_country_code
Categorical

High correlation 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.9 MiB
ke
313338 
ug
186641 
gb
 
21

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1000000
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowug
2nd rowug
3rd rowke
4th rowug
5th rowke

Common Values

ValueCountFrequency (%)
ke313338
62.7%
ug186641
37.3%
gb21
 
< 0.1%

Length

2025-11-06T14:28:02.873822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-06T14:28:02.988183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ke313338
62.7%
ug186641
37.3%
gb21
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
k313338
31.3%
e313338
31.3%
g186662
18.7%
u186641
18.7%
b21
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)1000000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
k313338
31.3%
e313338
31.3%
g186662
18.7%
u186641
18.7%
b21
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1000000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
k313338
31.3%
e313338
31.3%
g186662
18.7%
u186641
18.7%
b21
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1000000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
k313338
31.3%
e313338
31.3%
g186662
18.7%
u186641
18.7%
b21
 
< 0.1%

response_user_gender
Categorical

Missing 

Distinct2
Distinct (%)< 0.1%
Missing466152
Missing (%)93.2%
Memory size34.2 MiB
male
28615 
female
5233 

Length

Max length6
Median length4
Mean length4.3092059
Min length4

Characters and Unicode

Total characters145858
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfemale
2nd rowmale
3rd rowmale
4th rowfemale
5th rowmale

Common Values

ValueCountFrequency (%)
male28615
 
5.7%
female5233
 
1.0%
(Missing)466152
93.2%

Length

2025-11-06T14:28:03.118183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-06T14:28:03.235651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
male28615
84.5%
female5233
 
15.5%

Most occurring characters

ValueCountFrequency (%)
e39081
26.8%
m33848
23.2%
a33848
23.2%
l33848
23.2%
f5233
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)145858
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e39081
26.8%
m33848
23.2%
a33848
23.2%
l33848
23.2%
f5233
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)145858
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e39081
26.8%
m33848
23.2%
a33848
23.2%
l33848
23.2%
f5233
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)145858
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e39081
26.8%
m33848
23.2%
a33848
23.2%
l33848
23.2%
f5233
 
3.6%

response_user_dob
Date

Missing 

Distinct8157
Distinct (%)15.7%
Missing447888
Missing (%)89.6%
Memory size7.6 MiB
Minimum1917-12-07 00:00:00
Maximum2020-09-07 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-11-06T14:28:03.350156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:28:03.497320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct153536
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Memory size7.6 MiB
Minimum2014-11-28 08:05:19+00:00
Maximum2022-04-01 08:30:14.960459+00:00
Invalid dates0
Invalid dates (%)0.0%
2025-11-06T14:28:03.652814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:28:03.804603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2025-11-06T14:27:46.517909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:44.371809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:45.047088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:45.803102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:46.698783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:44.547402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:45.238201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:45.978716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:46.888666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:44.693917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:45.421708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:46.159547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:47.064990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:44.864420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:45.601333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2025-11-06T14:27:46.332940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2025-11-06T14:28:03.905767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
question_idquestion_user_country_codequestion_user_genderquestion_user_idquestion_user_statusresponse_idresponse_languageresponse_user_country_coderesponse_user_genderresponse_user_idresponse_user_status
question_id1.0000.1660.1120.6620.2820.9920.0210.1660.0700.6250.254
question_user_country_code0.1661.0000.0080.1570.2120.1670.2931.0000.0250.1700.193
question_user_gender0.1120.0081.0000.1220.0720.1090.0000.0080.0000.0670.043
question_user_id0.6620.1570.1221.0000.2000.6570.0160.1570.0600.4330.188
question_user_status0.2820.2120.0720.2001.0000.2810.0310.2120.0220.1930.136
response_id0.9920.1670.1090.6570.2811.0000.0230.1670.0690.6220.257
response_language0.0210.2930.0000.0160.0310.0231.0000.2930.0110.0270.028
response_user_country_code0.1661.0000.0080.1570.2120.1670.2931.0000.0250.1700.193
response_user_gender0.0700.0250.0000.0600.0220.0690.0110.0251.0000.1310.042
response_user_id0.6250.1700.0670.4330.1930.6220.0270.1700.1311.0000.170
response_user_status0.2540.1930.0430.1880.1360.2570.0280.1930.0420.1701.000

Missing values

2025-11-06T14:27:48.049456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2025-11-06T14:27:49.746931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-11-06T14:27:52.304584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

question_idquestion_user_idquestion_languagequestion_contentquestion_topicquestion_sentresponse_idresponse_user_idresponse_languageresponse_contentresponse_topicresponse_sentquestion_user_typequestion_user_statusquestion_user_country_codequestion_user_genderquestion_user_dobquestion_user_created_atresponse_user_typeresponse_user_statusresponse_user_country_coderesponse_user_genderresponse_user_dobresponse_user_created_at
7125941292395752341184engQ What vaccine can I use for my two weeks poultrypoultry2019-07-29 14:48:41.696704+00292468341917051engVaccinate against foul pox and coccidiosisNone2019-07-29 16:04:14.54143+00farmerzombieugNoneNone2019-07-29 14:45:56.686123+00farmerzombieugNoneNone2019-02-25 16:57:44.433512+00
2337096120640701082751engDo we have banana hybrid in Ugandabanana2018-09-26 14:47:57.686568+0012064864757555engQ108 Yes In Bushenyi DistrictNone2018-09-26 14:52:22.698027+00farmerliveugNoneNone2018-08-20 09:45:55.096378+00farmerliveugNoneNone2018-03-31 06:18:55.66669+00
116800285860121061566engQ hoW TO PLANT CABBAGEcabbage2018-08-11 12:05:42.179556+008586256472714engQ129 Just like sukumawiki, cabbages take the same process to plant.plant2018-08-11 12:11:01.808037+00farmerlivekeNoneNone2018-08-11 12:03:23.067669+00farmerlivekeNoneNone2017-10-26 17:47:11+00
4705029189490971041893engDononzio asks: my cow has aproblm it cann,t bleast feed their young one what can i do. Reply Q435 followed by your response.\n\noptout stop 6333cattle2018-12-12 11:25:23.516055+00190562121492749engAt fast provide bucket feeding and consult the veterinary.None2018-12-13 07:36:03.201454+00farmerzombieugNoneNone2018-08-07 09:45:11.23247+00farmerzombieugNoneNone2018-11-16 22:29:47.964895+00
6966053280867432260122engQ WHAT IS THE CORRECT AMOUNT OF A SIX ACRE LAND -FERTILIZER.None2019-07-07 12:59:54.864268+002808790936254engQ856 60KGSNone2019-07-07 14:06:26.08581+00farmerzombiekeNoneNone2019-07-07 12:56:09.701871+00farmerlivekefemale1997-07-222015-11-16 17:13:12+00
687531927698080804559engQ Other Than Fresian,jursey,borana Metion Other Names Of Cows You Know.cattle2019-06-27 15:34:56.701268+00277000182075087engQ6 CurnsNone2019-06-27 15:41:43.699797+00farmerlivekeNoneNone2018-04-23 11:58:50.562182+00farmerlivekeNoneNone2019-04-30 09:24:16.294116+00
10265148475459441682932engQ.Which is the most harmful disease in maize plantsmaize2020-09-29 13:56:05.573754+00475574182975907engReply Q15~Wilthing of maize plants caused by stalkborer(worm),it kills the plant and finally no yield/harvest. Thank you.maize2020-09-29 14:54:22.84647+00farmerlivekeNoneNone2018-12-11 11:55:31.454405+00farmerlivekeNoneNone2020-03-19 17:41:30.767385+00
4182699174932701294911engQ, what cozes splitting ov bananas in there old stage ov development when it is ready for harvesting?banana2018-12-01 07:41:57.789183+00174987911072318engQ47 It Depends On Type Of Soil ,None2018-12-01 07:56:15.488265+00farmerdestroyedugNoneNone2018-10-03 15:27:21.587963+00farmerliveugNoneNone2018-08-15 17:41:07.330389+00
8926109402281462918137engQ why are leguminous preferre for green manure?None2020-04-13 07:47:52.876696+00402336692520723engQ16 they prefer in green manure becouse green it decompose slowly in the farmeNone2020-04-13 10:15:19.078848+00farmerlivekeNoneNone2020-02-26 08:58:02.430389+00farmerlivekeNoneNone2019-09-26 17:51:35.860522+00
3258067149013601413665engWIC TYPE OV FERTILIZER IS ADVISABLE TO APLY IN BANANA PLANTATION?banana2018-11-05 08:22:43.028284+0014901715751622engQ358, use farm yard manureNone2018-11-05 08:30:13.53201+00farmerzombieugNoneNone2018-10-31 19:21:57.323151+00farmerliveugNoneNone2018-03-28 18:08:56.313601+00
question_idquestion_user_idquestion_languagequestion_contentquestion_topicquestion_sentresponse_idresponse_user_idresponse_languageresponse_contentresponse_topicresponse_sentquestion_user_typequestion_user_statusquestion_user_country_codequestion_user_genderquestion_user_dobquestion_user_created_atresponse_user_typeresponse_user_statusresponse_user_country_coderesponse_user_genderresponse_user_dobresponse_user_created_at
6655834266417661819939engWho can u cross breed chickenchicken2019-06-01 05:25:12.808348+00266572831816786engQ34 Aperson With A Good BreedNone2019-06-01 12:19:57.960275+00farmerzombieugNoneNone2019-01-11 07:40:36.222728+00farmerdestroyedugNoneNone2019-01-10 08:02:15.875999+00
5035958200541121724429engDiamethoade is used to treat cigar end rot in kales; cigar end rot is the rotting of kales stalks producing bad odours due to poor picking of the leaves.kale2018-12-28 17:08:08.67508+00200548941437652engQ130 so wotNone2018-12-28 17:25:31.020792+00farmerlivekeNoneNone2018-12-14 09:01:30.09489+00farmerlivekeNoneNone2018-11-08 14:01:34.442573+00
7879254333301572596524engQ how can i solve a problem of tomato brighttomato2019-10-21 08:48:50.462447+00333325941204171engQ144 spray using ridomilNone2019-10-21 10:17:44.159335+00farmerzombieugNoneNone2019-10-21 08:21:35.444754+00farmerliveugNoneNone2018-09-14 09:39:13.825308+00
1130391846787371917engWhich kind of trees that i as farmer can plant along the boundary, that may not affect my crops.tree2018-08-09 13:38:18.483454+008530618532089engQ117 THE TREES THAT U PLANT ALONG THE BOUNDARY IS SEVESEVEtree2018-08-10 14:15:42.750104+00farmerdestroyedkemaleNone2016-05-25 04:48:04+00farmerlivekeNoneNone2017-11-23 17:53:59+00
11329324556851073048311engWhat is the price of Chick marsh?chicken2021-04-22 17:25:33.779862+00557315851814926engQ74 Acording to our place. 5kg=250%2C 10kg%3D500%2C 50kg%3D1200 and 90kg is 1850%2F%3DNone2021-04-23 12:17:13.031618+00farmerlivekeNoneNone2020-04-16 17:59:05.407561+00farmerlivekeNoneNone2019-01-09 17:23:36.86069+00
7637680318928451074144enghow is onions propagated?onion2019-09-19 17:40:07.178611+00318968311573372engBy seed and later seedlingsNone2019-09-19 17:54:18.607449+00farmerzombieugNoneNone2018-08-15 19:56:54.121329+00farmerliveugNoneNone2018-11-30 13:07:10.180261+00
7450108308136132300714engWeldon Q Give me types of grass good for dairy cows,good for protains,vitamins?grass2019-08-29 16:32:09.003019+003081396592215engQ147 Lucerne,brachiari,boma rodes,Napier grass,gloves,napier-grass2019-08-29 16:34:08.091048+00farmerlivekeNoneNone2019-07-18 17:20:14.52606+00farmerlivekemale1990-01-152016-09-12 04:51:14+00
9618448441865032155417engWhat crop can i grow and earn income within this holiday and tell me the possible methods to use ?crop2020-07-03 17:48:33.54539+00443464812047285engQ89 Cabbagecabbage2020-07-07 16:55:05.879693+00farmerliveugNoneNone2019-05-26 17:47:13.214765+00farmerliveugNoneNone2019-04-16 11:49:35.598023+00
776110832482789555688engEverline asks: Is there any way I can boost my flowering beans after a heavy downpour of hailstones??? Reply Q471 followed by your response.bean2019-09-29 16:26:38.978063+00324833332149257engQ8,use forliar fertilizerNone2019-09-29 16:30:47.754327+00farmerzombiekeNoneNone2017-11-30 17:22:06+00farmerdestroyedkeNoneNone2019-05-23 17:29:12.86036+00
564968922267914475244engHOW CAN I KEEP THEM FROM DENGERS.None2019-03-06 04:40:04.794134+0022275907638307engQ185 by use of techinical know how makernizms to protect the may come problem.None2019-03-06 09:27:56.944099+00farmerdestroyedugNoneNone2017-10-28 10:20:48+00farmerliveugNoneNone2018-01-23 17:52:20+00